World Economic Forum Bubble Early Warning System

Center for Real Estate Finance Research December 2015

PROF. STIJN VAN NIEUWERBURGH

Faculty Adviser Director of the the

Center for Real Estate Finance Research

Our Team

2

CAITLYN DEWITT Faculty Fellow

MBA2

DWANE JONES Faculty Fellow

MBA1

SANAM MECHKAT Faculty Fellow

MBA1

Big Picture: the World Economic Forum’s initiative on an early warning system for the detection of real estate bubbles. • Goal of the overall project

• Can we create a model that would tell us whether we are in a real estate bubble, i.e. whether current prices have deviated unjustifiably from the fundamental value of the underlying property?

• Determine whether we can use data that we have access to in order to correctly identify a bubble in individual metros and the nation

• NYU Scope • In order to shed light on whether the current boom is a bubble, we use data (total returns, income yields)

from U.S. equity REITs and transactional data to calculate implied dividend growth expectations

Research Objectives

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Real Estate Market A Brief Introduction

Defining a Bubble

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There is no agreed upon definition for a bubble and any definition must distinguish itself from a cycle

If we had to define it, what’s a bubble? In economics, a bubble is formed when trade in an asset drives prices so high up that they no longer reflect the asset’s intrinsic (justified or fundamental) value and instead appear based on implausible or inconsistent views of the future

Why are real estate bubbles so dangerous? Real estate is a major storage of personal wealth and a sudden decline in prices can cut the wealth of households, affect retirement plans, and destabilize the economy

How do we spot one? As it is difficult to determine intrinsic value, bubbles are often only spotted in retrospect (i.e. too late) when prices drop

How REITS work

Data sources: REITS and Transactional Cap Rates • U.S. REITS are good proxies for the overall valuation dynamics in

commercial real estate Steps 1. Calculate the expected returns for REITS

• Dynamic five-factor model with stock, bond, value, size, and momentum returns as inputs

• Run a regression model for risk premia, i.e. expected excess returns, on REITS, and add risk-free rate to get expected returns

2. Calculate investors’ expectations about future dividend (NOI) growth using a present-value model (Campbell and Shiller, 1989)

• Using the time series of expected returns (Step 1) and the time series of observed price-dividend ratios (inverse cap rates) from REITS

3. Back out the market perception of dividend NOI growth over the next 10 years in order to justify the current valuation ration and given the current expected return

4. Analyze expected dividend growth on REITS to see how they compare to the long-term average growth rate

Valuing Real Estate Investments: Value = Net Operating Income Cap Rate Cap rate = r – g

• Capitalization rate is the rate of return on a real estate investment property based on the income that the property is expected to generate.

Cap rate is the difference between: • PV of the sum of expected future returns, r • PV of the sum of expected future dividend (NOI) growth, g

Methodology

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Data Summary + Takeaways

Data Summary: Metropolitan

National expected annual dividend growth over next 10 years The graph above shows that the market currently expects dividend growth on REITS to be at around 15% per year (for the next 10 years). This is not only aggressive in absolute terms, but it is also high relative to the long-term average growth rate of 3.0% (solid red line) and relative to the implied growth rate over the past 30 years. The implied growth assumptions priced in are at the same level as they were in 2007 at the peak of the boom.

Data Summary: National

Users of Data

Some Key Takeaways • Scalability and flexibility of the model • Model for the “public good” • Potential for public-private partnership via information sharing and application

Next Steps

• NYU portion incorporated into Newmark Grubb Knight Frank research • 2016 World Economic Forum Annual Meeting in Davos, Switzerland, 20-23 January

• Theme: Mastering the Fourth Industrial Revolution • Further applications:

• Potential application to the residential real estate market sector

Key Takeaways and Next Steps

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Q&A